rriskDistributions-package {rriskDistributions}

Fitting distributions to given data or known quantiles

Description

This packages provides a collection of functions for estimation parameters of continuous or discrete distributions (related to the rrisk project) to given data or to known quantiles.

Details

This package is a part of the rrisk project and contains functions for fitting distributions to given data or by known quantiles. This package does not depend on the whole rrisk project and can be used separately. The rrisk project can be downloaded from http://www.bfr.bund.de/cd/52158.

The main functions fit.perc and fit.cont call a GUI that allows users to choose an appropriate distribution family to given data or to known quantiles without any knowledge of the R syntax.

Note

Fitting by given quantiles: a typical application is the definition of a distribution based on expert opinion on some quantiles (e.g., the 2.5th, median and 97.5th) of the trial to be modelled. rrisk has a functionality, to fit all continuous or discrete distributions simultaneously without urging the user to specify the distribution family in advance.

Author(s)

Natalia Belgorodski [e-mail] (STAT-UP Statistical Consulting),
Matthias Greiner [e-mail] (Federal Institute for Risk Assessment, Germany),
Kristin Tolksdorf [e-mail] (Federal Institute for Risk Assessment, Germany),
Katharina Schueller [e-mail] (STAT-UP Statistical Consulting)

Examples

q <- stats::qweibull(p = c(0.025, 0.5, 0.975), shape = 2, scale = 3)
get.weibull.par(q = q)
q <- stats::qweibull(p = c(0.025, 0.5, 0.975), shape = 0.01, scale = 1)
get.weibull.par(q = q)

p <- c(0.025, 0.50, 0.975)
q <- c(9.68, 29.2, 50.98)
fit.results <- rriskFitdist.perc(p, q, show.output = FALSE)
plotDiagnostics.perc(fit.results)

p <- c(0.25, 0.50, 0.75)
q <- c(9.68, 29.2, 50.98)
fit.results <- rriskFitdist.perc(p, q, show.output = FALSE)
plotDiagnostics.perc(fit.results)
plotDiagnostics.perc(fit.results, tolPlot = 2)

## Not run: 
  if( class(tcltk::tclRequire("Tktable")) == "tclObj" ) {
    res.fitcont <- fit.cont(data2fit = rnorm(100))
    res.fitcont
  }
  if( class(tcltk::tclRequire("Tktable")) == "tclObj" ) {
    res.fitperc <- fit.perc()
    res.fitperc
  }

## End(Not run)